Ladislav Rampásek

According to our database, Ladislav Rampásek authored at least 16 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Graph Positional and Structural Encoder.

Renming Liu, Semih Cantürk, Olivier Lapointe-Gagné, Vincent Létourneau, Guy Wolf, Dominique Beaini, Ladislav Rampásek

CoRR, 2023

Attending to Graph Transformers.

Luis Müller, Mikhail Galkin, Christopher Morris, Ladislav Rampásek

CoRR, 2023

GPS++: Reviving the Art of Message Passing for Molecular Property Prediction.

Dominic Masters, Josef Dean, Kerstin Klaser, Zhiyi Li, Sam Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Andrew W. Fitzgibbon, Shenyang Huang, Ladislav Rampásek, Dominique Beaini

CoRR, 2023

2022

GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property Prediction.

Dominic Masters, Josef Dean, Kerstin Klaser, Zhiyi Li, Sam Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Ladislav Rampásek, Dominique Beaini

CoRR, 2022

Taxonomy of Benchmarks in Graph Representation Learning.

Renming Liu, Semih Cantürk, Frederik Wenkel, Dylan Sandfelder, Devin Kreuzer, Anna Little, Sarah McGuire, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek

CoRR, 2022

Recipe for a General, Powerful, Scalable Graph Transformer.

Ladislav Rampásek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Long Range Graph Benchmark.

Vijay Prakash Dwivedi, Ladislav Rampásek, Michael Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Taxonomy of Benchmarks in Graph Representation Learning.

Renming Liu, Semih Cantürk, Frederik Wenkel, Sarah McGuire, Xinyi Wang, Anna Little, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek

Proceedings of the Learning on Graphs Conference, 2022

2021

Towards a Taxonomy of Graph Learning Datasets.

Renming Liu, Semih Cantürk, Frederik Wenkel, Dylan Sandfelder, Devin Kreuzer, Anna Little, Sarah McGuire, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek

CoRR, 2021

Hierarchical Graph Neural Nets can Capture Long-Range Interactions.

Ladislav Rampásek, Guy Wolf

Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

2020

Latent-variable models for drug response prediction and genetic testing.

Ladislav Rampásek

PhD thesis, 2020

2019

Dr.VAE: improving drug response prediction via modeling of drug perturbation effects.

Ladislav Rampásek, Daniel Hidru, Petr Smirnov, Benjamin Haibe-Kains, Anna Goldenberg

Bioinform., 2019

2017

Dropout Feature Ranking for Deep Learning Models.

Chun-Hao Chang, Ladislav Rampásek, Anna Goldenberg

CoRR, 2017

2016

RNA motif search with data-driven element ordering.

Ladislav Rampásek, Randi M. Jimenez, Andrej Lupták, Tomás Vinar, Brona Brejová

BMC Bioinform., 2016

Cell-free DNA fragment-size distribution analysis for non-invasive prenatal CNV prediction.

Aryan Arbabi, Ladislav Rampásek, Michael Brudno

Bioinform., 2016

2014

Probabilistic method for detecting copy number variation in a fetal genome using maternal plasma sequencing.

Ladislav Rampásek, Aryan Arbabi, Michael Brudno

Bioinform., 2014